조명전기설비학회논문지 (Journal of the Korean Institute of Illuminating and Electrical Installation Engineers)

  • 제19권3호
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  • Pages.119-126
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  • 2005
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  • 1229-4691(pISSN)
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  • 2287-5034(eISSN)
한국조명전기설비학회 (The Korean Institute of IIIuminating and Electrical Installation Engineers)
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Electrical Resistance Tomography의 영상복원 기법의 비교

A Comparison of Image Reconstruction Techniques for Electrical Resistance Tomography

  • 김호찬 (제주대학교 전기전자공학부) ;
  • 부창진 (제주대학교 전기전자공학부) ;
  • 이윤준 (제주대학교 전기전자공학부)
  • 발행 : 2005.05.01
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초록

Electrical resistance tomography(ERT)는 적절하게 설계된 전류를 대지 지하에 주입하여 이에 따른 인가전압을 대지 경계에서 측정한 후 이를 근거로 ERT의 영상복원 알고리즘에서 대지 지하의 대지저항률 분포를 얻고 대지 지하에 뭍힌 물체를 크기와 위치, 그리고 저항률에 대한 특성을 파악할 수 있는 기술이다. 본 논문에서는 ERT의 영상복원 기법으로 Gauss-Newton, TLS와 SIRT 방법들을 살펴본다. 컴퓨터 시뮬레이션을 통해 TLS 방법을 이용한 ERT 영상복원의 성능이 Gauss-Newton와 SIRT방법에 의해 얻어진 결과보다 향상되는 것을 보이도록 한다.

Electrical resistance tomography(ERT) maps resistivity values of the soil subsurface and characterizes buried objects. The characterization includes location, size and resistivity of buried objects. In this paper, Gauss-Newton, truncated least squares(TLS) and simultaneous iterative reconstruction technique(SIRT) methods are presented for the solution of the ERT image reconstruction. Computer simulations show that the spatial resolution of the reconstructed images by the TLS approach is improved as compared to those obtained by the Gauss-Newton and SIRT method.

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참고문헌

  1. Y. Sasaki, 'Resolution of resistivity tomography inferred from numerical simulation,' Geophysical Prospecting, Vol. 57, pp. 1270-1281, 1992
  2. D.W. Oldenberg and Y. Li, 'Estimating of investigation in DC resistivity and IP survey,' Geophysics, Vol. 64, No. 2, pp. 403-416 1999 https://doi.org/10.1190/1.1444545
  3. M.H. Loke, and T. Dahlin, 'A comparison of the Gauss-Newton and quasi-Newton methods in resistivity imaging inversion,' Journal of Applied Geophysics, Vol. 49, pp. 149-162, 2002 https://doi.org/10.1016/S0926-9851(01)00106-9
  4. C.R. Vogel, Computational methods for inverse problems, Society for Industrial and Applied Mathematics 2002
  5. A.C. Tripp, G.W. Hohmann, and C.M. Swift Jr., 'Two-dimensional resistivity inversion,' Geophysics, Vol. 49, pp. 1708-1717, 1984 https://doi.org/10.1190/1.1441578
  6. L.R. Lines and S. Treitel, 'Tutorial : A review of least squares inversion and its application to geophysical problems,' Geophysical Prospecting, Vol. 32, pp. 159-186, 1984 https://doi.org/10.1111/j.1365-2478.1984.tb00726.x
  7. T. Yoshinaga, 'A fast convergence method with simultaneous iterative reconstruction technique for computerized tomography,' Int. J. Imag. Syst. and Technol., Vol. 10, No. 6, pp. 432-436, 1999 https://doi.org/10.1002/(SICI)1098-1098(1999)10:6<432::AID-IMA4>3.0.CO;2-I
  8. A. Tarantola and B. Valette, 'Generalized nonlinear inverse problems solved using least squares criterion,' Rev. Geophys. Space Phys., Vol. 20, pp. 219-232, 1982 https://doi.org/10.1029/RG020i002p00219
  9. I. Brunner, S. Friedel, F. Jacobs, and E. Danckwardt, 'Investigation of a Tertiary maar structure using three-dimensional resistivity imaging,' Geophys. J. Int., Vol. 136, pp. 771-780, 1999 https://doi.org/10.1046/j.1365-246x.1999.00770.x
  10. G.A. Kyriacou, C.S. Koukourlis, J.N. Sahalos, and K. Batas, 'Reconstruction of impedance images using a modified perturbation method,' Clin. Physiol. Meas., Vol. 13, pp. 91-94, 1992 https://doi.org/10.1088/0143-0815/13/A/018